{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:47Z","timestamp":1747216187781,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643685335"}],"license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,22]]},"abstract":"<jats:p>This paper presents a chatbot that simplifies accessing and understanding the open-access records of adverse events related to medical devices in the MAUDE database. The chatbot is powered by generative AI technology, enabling count and search queries. The chatbot uses the openFDA API and GPT-4 model to interpret users\u2019 natural language queries, generate appropriate API calls, and summarize adverse event reports. The chatbot also provides a downloadable link to the original reports. The model\u2019s performance in generating accurate API calls was assessed and improved by training it with few-shot examples of query-URL pairs. Additionally, the quality of content-based summaries was evaluated by human expert ratings. This initiative is a significant step towards making patient safety data accessible, replicable, and easily manageable by a broader range of researchers.<\/jats:p>","DOI":"10.3233\/shti240639","type":"book-chapter","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:10:05Z","timestamp":1724407805000},"source":"Crossref","is-referenced-by-count":0,"title":["Developing a Generative AI-Powered Chatbot for Analyzing MAUDE Database"],"prefix":"10.3233","author":[{"given":"Yue","family":"Yu","sequence":"first","affiliation":[{"name":"University of Texas Health Science Center at Houston, Houston, Texas, USA"}]},{"given":"Yuheng","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston, Houston, Texas, USA"}]},{"given":"Yubo","family":"Feng","sequence":"additional","affiliation":[{"name":"Vanderbilt University, Nashville, Tennessee, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0864-8368","authenticated-orcid":false,"given":"Yang","family":"Gong","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston, Houston, Texas, USA"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Health and Informatics Innovations for Sustainable Health Care Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240639","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:10:05Z","timestamp":1724407805000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240639"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"ISBN":["9781643685335"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240639","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}